An efficient and flexible inference system for serving heterogeneous ensembles of deep neural networks. - Pierrick Pochelu; Serge G. Petiton; Bruno Conche (IEEE BigData, 2021)

Distributed Ensembles of Reinforcement Learning Agents for Electricity Control. - Pierrick Pochelu; Bruno Conche; Serge G. Petiton (COINS, 2022)

A Deep Neural Networks ensemble workflow from hyperparameter search to inference leveraging GPU clusters. - Pierrick Pochelu; Serge G. Petiton; Bruno Conche (HPC Asia, 2022)

Weakly Supervised Faster-RCNN+FPN to classify animals in camera trap images. - Pierrick Pochelu; Clara Erard; Philippe Cordier; Serge G. Petiton; Bruno Conche (IVSP, 2022)

Deep Learning Inference Frameworks Benchmark. - Pierrick Pochelu (CoRR, 2022)

Ensembles of Deep Neural Networks distributed and parallel for the energy industry. (Ensembles de réseaux de neurones répartis et parallèles appliqués au domaine de l'énergie). - Pierrick Pochelu (2022)

Mastering Computer Vision Inference Frameworks. - Pierrick Pochelu; Oscar Castro-López (ICPE (Companion), 2024)

JaxDecompiler: Redefining Gradient-Informed Software Design. - Pierrick Pochelu (CoRR, 2024)